Human migration is a constant phenomenon in human history, and its study involves numerous research fields. To date, data not typically used for studying migration are increasingly available. These include the so-called social Big Data: digital traces left by humans through cell phones, online social networks, and online services. More and more technologies can be employed to extract information from these large datasets. However, how can Big Data help to understand the migration phenomenon?
How did the COVID-19 epidemics change our mobility habits, and how did it impact on people’s well-being and on the virus transmissibility?
In the first webinar of the seminar series organized by SoBigData, we will address these questions, as well as many others, from the perspective of Data Science and Environmental Epidemiology.
Sentiment Analysis is a sub-field of Natural Language Processing (NLP) that, combining tools and techniques from Linguistics and Computer Science, aims at systematically identifying, extracting, and studying emotional states and personal opinion in natural language.
Women's football took its first steps since the early twentieth-century. Unfortunately, the ostracism from the English Football Association drastically slowed down its development, which experienced a long period of stagnation. Women's football resurfaced in the 1960s in the Nordic countries of Europe, and it is now spreading all over the world. From 2012 the number of women academies has doubled, with around 40 million girls and women playing football worldwide nowadays.
Thanks to the wide diffusion of localization technologies and mobile services based on the positioning of users and devices, the availability of mobility traces is increasing fast in several application domains. Location-based services provided through smartphones are nowadays extremely popular and the vast amounts of data that this trend leads to produce and collect open the door to several opportunities of converting them into better services, economical returns, more sustainable cities, improved living conditions, etc.
The rapid dynamics of COVID-19 calls for quick and effective tracking of virus transmission chains and early detection of outbreaks, especially in the phase 2 of the pandemic, when lockdown and other restriction measures are progressively withdrawn, in order to avoid or minimize contagion resurgence. For this purpose, contact-tracing apps are being proposed for large scale adoption by many countries.
The Council of Europe and the University of Strasbourg organised the 5th edition of the "AI Breakfast" in the form of a webinar on 16 April 2020.
Three experts were brought together on the topic of tracking applications on mobile phones in the fight against COVID-19. Michael Veale, Lecturer at University College London, Dino Pedreschi, Professor of Computer Science at the University of Pisa and Adrien Basdevant, a data protection lawyer, discussed the myths and realities of these applications.
Alex Bravo Serrano TNA's experience in GATE, Sheffield, UK
As the amount of user generated content in social media is increasing at an exponential pace, detecting offensive language and harmful content automatically in an efficient way is a very important issue for the society. The offensive language can be expressed in various forms such as hate speech, cyberbullying, profanity and harassment, which has negative effects especially in adolescents.
ETHZ and SoBigData are organizing a Real Time Epidemic Datathon
What is "Epidemic Datathon"?
It is a collective open source real-time forecasting challenge that aims at joining forces to develop real-time and large-scale epidemic forecasting models.